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While data has become the life-blood of most business, the state of data quality continues to be a big challenge as they look to increase revenue, reduce cost and improve customer interaction. 70% of companies suffer from common data errors. The most common data errors are incomplete data, outdated information and duplicate data. And data is growing at a rapid rate. The BIG DATA deluge is such that human beings cannot be expected to spot patterns in the data. Nor can they grasp the size and complexity of one dataset and see how it relates to another. Most business executives agree that bad data is costing them millions of dollars every year. DATA is a critical underpinning of nearly any initiative focused on employees, customers, products, suppliers, and other CEO priorities.

Most firms estimate that they are only analyzing 12% of the data that they have today. What happens to the other 88%? This gap illustrates the enormous amount of possibility for your business. We are at a tipping point where the emergence of cloud, new design paradigms, and advances in analytics mean data-driven decisions can now be an essential daily activity for IT and business people alike.

While organisations are starting to embark on the BIG DATA and Analytics journey, they are struggling to identify bad data and quantify the cost of bad data.

So, what are the reasons for inaccuracy?

chart1The level of inaccurate data is staggering when one considers how much businesses are relying on information for business intelligence and improved customer interaction

Collectively, 78 percent of companies have problems with the quality of data they collect from various channels. Globally, call centers produce the poorest data quality, followed by websites.

The level of inaccurate data relates to a lack of a sophisticated data management strategy, which many organizations are struggling to centralize.

What type of data are most susceptible to quality problems?chart2

Almost all types, mostly master data.

What is the business impact of bad data?chart3

Bad decisions and ultimately, loss of revenue and reputation.

What are the benefits of good data?

  • Best Practices in data quality can boost revenue by 30%
  • A data strategy that solves conflicts at the source can lead to a 40% increase in converting inquiries to marketing qualified leads
  • Clean data can reduce contact build time with a prospect by 5%
  • Those organisations that have made improvements to data quality processes in the past 2 years have increased their profits by 20%

Remember, Good Data is a pre-requisite for BIG DATA Analytics.

What is the Solution?

Data Profiling allows the users to look for patterns in data which often reveals issues the business world would not have been aware of and then drilling down into what could be the root cause. It helps in uncovering the bigger picture and building the business case for a more effective data quality initiative. Using tangible business measures like revenue or customer satisfaction to depict the impact of inaccurate data can make a compelling business case to fix the data quality problems, which is a pre-requisite for any Data Analytics initiative.

To determine the current state of your data, simply upload a file with 10,000 rows and we will send you the results within 24 hours. See “How it works” for more information and Sample reports.